ci-optimize

ci-optimize is a command for coding agents from dykyi-roman/awesome-claude-code. It costs 23 tokens per session (1,013 once invoked), scanned A, original, MIT.

A command for analyzing and improving the speed of a continuous integration pipeline. It examines caching, parallel jobs, job dependencies, and other parts of the CI configuration.

In plain words
What is it for?
Use it to inspect GitHub Actions or GitLab CI configuration and focus on tasks such as caching, parallelizing tests, or reducing Docker build time.
Why use it?
It helps identify why automated checks take too long and where the pipeline is wasting time.

Command

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add commands/dykyi-roman/awesome-claude-code/ci-optimize
Clone the repo
git clone --depth 1 https://github.com/dykyi-roman/awesome-claude-code

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for ci-optimize

README.md
[![agentmods](https://agentmods.dev/badge/commands/dykyi-roman/awesome-claude-code/ci-optimize.svg)](https://agentmods.dev/commands/dykyi-roman/awesome-claude-code/ci-optimize)
Your own site
<a href="https://agentmods.dev/commands/dykyi-roman/awesome-claude-code/ci-optimize"><img src="https://agentmods.dev/badge/commands/dykyi-roman/awesome-claude-code/ci-optimize.svg" alt="Measured on agentmods" height="20"></a>
Per session 23 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,013 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00023 $0.01013
Opus 5 $0.00012 $0.00507
Sonnet 5 $0.00005 $0.00203
Haiku 4.5 $0.00002 $0.00101

Measured today against content hash b3726660de0c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ci-optimize scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

commands/ci-optimize.md · 168 lines

How it starts

The opening of the file, as written. The whole thing — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Optimize CI Pipeline

Improve CI/CD pipeline performance by analyzing and optimizing caching, parallelization, and job structure.

Input Parsing

Parse $ARGUMENTS to extract path and optional focus areas:

Format: [path] [-- <focus-areas>]

Examples:
- /acc:ci-optimize
- /acc:ci-optimize ./
- /acc:ci-optimize -- focus on caching
- /acc:ci-optimize ./ -- reduce Docker build time
- /acc:ci-optimize -- parallelize tests, optimize lint

Parsing rules:

  1. Split $ARGUMENTS by -- (space-dash-dash-space)
  2. First part = positional arguments, Second part = meta-instructions (focus areas)
  3. In positional arguments, extract path (optional, defaults to ./)
  4. After -- = focus areas (optional optimization targets)
  5. If no path provided, default to current directory (./)
  6. Validate path exists before proceeding

Pre-flight Check

  1. Find CI configuration:

    ls .github/workflows/*.yml 2>/dev/null
    ls .gitlab-ci.yml 2>/dev/null
    
  2. If no CI found:

    • Suggest running /acc:ci-setup first
  3. Check for optimization targets:

    # Check for caching
    grep -r "cache" .github/workflows/ .gitlab-ci.yml 2>/dev/null
    
    # Check job dependencies
    grep -rE "(needs:|depends_on:)" .github/workflows/ .gitlab-ci.yml 2>/dev/null
    
    # Check for Docker
    ls Dockerfile* 2>/dev/null
    

Instructions

Use the acc:ci-coordinator agent to optimize:

Task tool with subagent_type="acc:ci-coordinator"
prompt: "Optimize CI pipeline at [PATH].

Operation: OPTIMIZE

[FOCUS_AREAS if provided]

Analysis targets:
1. Caching efficiency
2. Job parallelization
3. Dependency structure
4. Docker build optimization
5. Resource usage

Provide:
- Current vs optimized comparison
- Specific changes to make
- Estimated time savings"

Expected Output

The coordinator will:

  1. Analyze current pipeline:

    • Total execution time
    • Critical path
    • Parallelism percentage
    • Cache hit rates
  2. Identify bottlenecks:

    • Slowest jobs
    • Sequential when parallel possible
    • Cache misses
    • Unnecessary waits

Read the full file on GitHub · 168 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. today First seen · 168 lines · 0 tokens per session scan A b3726660de0c

Subscribe to this mod's changes

ci-optimize is a command published in the GitHub repository dykyi-roman/awesome-claude-code (96 stars, last pushed 19d ago), licensed MIT. It adds 23 tokens to every session and 1,013 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.